Collection
Application Reviews and Case Studies (ARCS)
Application Reviews and Case Studies (ARCS) is a distinct section of Psychometrika. It is devoted to highlighting the essential connection between novel methodology and its application to empirical data in psychology, education, and related areas in the social sciences in a way that deepens the substantive understanding of underlying phenomena in one of these disciplines. Manuscripts published in ARCS are expected to be methodologically rigorous and illustrate the application of innovative methodology with one or more real data examples of general interest to educational, psychological, social, or behavioral scientists. Manuscripts focused on novel applications of an existing method are also encouraged.
Editors
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Nidhi Kohli
PhD, University of Minnesota, USA
Articles (27 in this collection)
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Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments
Authors (first, second and last of 4)
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A Latent Variable Mixed-Effects Location Scale Model with an Application to Daily Diary Data
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Computation and application of generalized linear mixed model derivatives using lme4
Authors (first, second and last of 4)
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Transformer-Based Deep Neural Language Modeling for Construct-Specific Automatic Item Generation
Authors (first, second and last of 5)
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A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data
Authors (first, second and last of 5)
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Better Information From Survey Data: Filtering Out State Dependence Using Eye-Tracking Data
Authors (first, second and last of 4)
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On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence
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Matching IRT Models to Patient-Reported Outcomes Constructs: The Graded Response and Log-Logistic Models for Scaling Depression
Authors (first, second and last of 5)
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Certainty-Based Marking on Multiple-Choice Items: Psychometrics Meets Decision Theory
Authors (first, second and last of 7)
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Combining Clickstream Analyses and Graph-Modeled Data Clustering for Identifying Common Response Processes
Authors (first, second and last of 7)
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Trivariate Theory of Mind Data Analysis with a Conditional Joint Modeling Approach
Authors (first, second and last of 4)
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Modeling Intensive Polytomous Time-Series Eye-Tracking Data: A Dynamic Tree-Based Item Response Model
Authors (first, second and last of 4)
